Size distribution determination of aerosols using hyperspectral image technology and analytics

ABSTRACT

An aerosol distribution determining system and method are provided. The system includes a set of light emitters for emitting electromagnetic radiation. The system further includes a hyperspectral imaging camera for capturing hyperspectral images of the electromagnetic radiation in an absence of and in a presence of an aerosol distribution. The system also includes a data processing system for determining at least one of a size, a vertical density distribution, and a shape of particles in the aerosol distribution based on a spectral response, an angular distribution, and a polarization of the aerosol distribution derived using the hyperspectral images.

BACKGROUND

Technical Field

The present invention relates generally to information processing and,in particular, to size distribution determination of aerosols usinghyperspectral image technology and analytics.

Description of the Related Art

Fine particle pollution or PM2.5 describes particulate matter that is2.5 micrometers in diameter and smaller. The increase of PM2.5 classparticles in the atmosphere is a source of great concern and hastriggered government programs directed to obtaining more reliablemeasurements of such particles in order to generate better emissioncontrol methods.

Current detection methods for PM2.5 include the use of satelliteimaging. In particular, satellite imaging has been used to determinesource distribution and evolution of aerosols. However, satellite datahas elements that are dependent on soil reflectivity and atmosphericconditions and thus require extensive analyses. Furthermore, for somedeterminations, the geographical reach and spatial resolution providedby satellite data acquisition is not sufficient to provide adequatedetection of PM2.5.

For example, PM2.5 distribution detection for certain applications suchas at the urban center level require PM2.5 distribution detection at thestreet or neighborhood level. Satellites acquire reflections in a verylarge column of atmosphere where lower and higher levels of theatmosphere contribute to the reflection. Extracting information andlocalizing particle distribution as function of height is challenging.In many cases, a fusion of data provided from a satellite and calibratedat the local level is required.

The use of satellites for PM2.5 distribution detection is a continuouslyevolving technology due to improvements in image detection techniques.The spatial resolution of such detection is on the kilometer scale anddata is acquired every day or sparser. However, for some determinationsof geographical reach, the resolution provided by satellite dataacquisition is not sufficient. This is typically the case in large urbanareas or industrial locations where dust variations across a fewkilometers can be significant and can be affected by buildings, streets,and so forth. Moreover, the particle distributions in such scenarios arestrongly correlated with traffic patterns and/or construction sites.

Thus, there is a need for improved size distribution determination ofaerosols involving PM2.5.

SUMMARY

According to an aspect of the present principles, an aerosoldistribution determining system is provided. The system includes a setof light emitters for emitting electromagnetic radiation. The systemfurther includes a hyperspectral imaging camera for capturinghyperspectral images of the electromagnetic radiation in an absence ofand in a presence of an aerosol distribution. The system also includes adata processing system for determining at least one of a size, avertical density distribution, and a shape of particles in the aerosoldistribution based on a spectral response, an angular distribution, anda polarization of the aerosol distribution derived using thehyperspectral images.

According to another aspect of the present principles, a method foraerosol distribution determination is provided. The method includesemitting, by a set of light emitters, electromagnetic radiation. Themethod further includes capturing, by a hyperspectral imaging camera,hyperspectral images of the electromagnetic radiation in an absence ofand in a presence of an aerosol distribution. The method also includesdetermining, by a data processing system, at least one of a size, avertical density distribution, and a shape of particles in the aerosoldistribution based on a spectral response, an angular distribution, anda polarization of the aerosol distribution derived using thehyperspectral images.

According to yet another aspect of the present principles, a computerprogram product for aerosol distribution determination is provided. Thecomputer program product includes a non-transitory computer readablestorage medium having program instructions embodied therewith. Theprogram instructions are executable by a computer to cause the computerto perform a method. The method includes emitting, by a set of lightemitters, electromagnetic radiation. The method further includescapturing, by a hyperspectral imaging camera, hyperspectral images ofthe electromagnetic radiation in an absence of and in a presence of anaerosol distribution. The method also includes determining, by a dataprocessing system, at least one of a size, a vertical densitydistribution, and a shape of particles in the aerosol distribution basedon a spectral response, an angular distribution, and a polarization ofthe aerosol distribution derived using the hyperspectral images.

These and other features and advantages will become apparent from thefollowing detailed description of illustrative embodiments thereof,which is to be read in connection with the accompanying drawings.

BRIEF DESCRIPTION OF DRAWINGS

The disclosure will provide details in the following description ofpreferred embodiments with reference to the following figures wherein:

FIG. 1 shows an exemplary processing system 100 to which the presentprinciples may be applied, in accordance with an embodiment of thepresent principles;

FIG. 2 shows an exemplary system 200 for determining the size of adistribution of aerosols;

FIG. 3 shows a top view of the laser diode array 220 of FIG. 2, inaccordance with an embodiment of the present principles;

FIGS. 4-6 show an exemplary method 400 for determining the size of adistribution of aerosols using white laser diodes, in accordance with anembodiment of the present principles;

FIGS. 7-9 shows an exemplary method 700 for determining the size of adistribution of aerosols using colored laser diodes or white laserdiodes with narrow bandpass filters and polarization filters in front ofthe white laser diodes, in accordance with an embodiment of the presentprinciples;

FIG. 10 shows a system 1000 for determining the size of a distributionof aerosols, deployed in an exemplary scenario 1077, in accordance withan embodiment of the present principles;

FIG. 11 shows a system 1100 for determining the size of a distributionof aerosols, deployed in an exemplary scenario 1177, in accordance withan embodiment of the present principles; and

FIG. 12 shows a system 1200 for determining the size of a distributionof aerosols, deployed in an exemplary scenario 1277, in accordance withan embodiment of the present principles.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The present principles are directed to size distribution determinationof aerosols using hyperspectral image (HIS) technology and analytics.

In an embodiment, the present principles utilize hyperspectral imagingtechnology for the local determination of aerosol distribution withinthe PM2.5 classification. In an embodiment, the present principles useone or more static emission points that are distributed on the groundand a mobile or stationary camera(s).

In an embodiment, the present principles provide a way to determine thesize of a distribution of aerosols by observing the MIE scatting from acollimated light source using hyperspectral imaging.

In an embodiment, the present principles can exploit the road mapcapability of hyperspectral imaging, which makes it possible to create avery complex hyperspectral cube using light weight, low power, and fastsnapshot cameras. Images from laser diodes and their halo are taken byhyperspectral cameras mounted on various vehicles/objects. A laser diodearray is distributed in height by attachment to poles or to panels beingsuspended by a device capable of flight. The laser diode array can alsobe distributed on the ground for column assessment from a plane,helicopter, drone, and so forth.

The present principles described here allow a high density measurementsacross a distribution of locations where diodes and blackbody disks canbe positioned on buildings, cell towers, hospitals, schools, and otherplaces/objects with well knows geospatial locations. Using a mobiledetector, a large number of sensors can be covered in a short period oftime by programming the data collection vehicles (e.g., planes,helicopters, drones, and so forth) to travel on a well-defined path. Thepresent principles can detect aerosols, dust, pollution plumes,chemicals (such as, e.g., but not limited to, methane, CO2, and soforth), and so forth. The detection range is dependent upon the datacollection vehicle/object. In an embodiment, the collection range can bein hundreds of feet, corresponding to the height of drone flying. It isto be noted that pollution at such height is affecting population healthand the densest distribution is likely to be found in this range.

In an embodiment, the spectral response, angular distribution, and thepolarization are used to extract information about particle size,vertical density distribution and shape of particles. The signal is alsoverified against a library of well-known spectra that are obtained in alaboratory using calibrated instruments that are not usually portable.The laboratory data set is used to increase the confidence in acquireddata from a discrete number of wavelengths and to assign the correctparticulates in size, density and chemical composition.

In an embodiment, once a calibration of a point is obtained outside(where we have a well-defined wavelength diode), the identified particlesize and composition can be extrapolated to the surroundings. This wouldbe similar to, for example, a large image where one or multiple pointsserve as a calibration point and all other points will be assigned asimilar distribution but the variation of the signal will be attributedto spatial variation in density.

FIG. 1 shows an exemplary processing system 100 to which the presentprinciples may be applied, in accordance with an embodiment of thepresent principles. The processing system 100 includes at least oneprocessor (CPU) 104 operatively coupled to other components via a systembus 102. A cache 106, a Read Only Memory (ROM) 108, a Random AccessMemory (RAM) 110, an input/output (I/O) adapter 120, a sound adapter130, a network adapter 140, a user interface adapter 150, and a displayadapter 160, are operatively coupled to the system bus 102.

A first storage device 122 and a second storage device 124 areoperatively coupled to system bus 102 by the I/O adapter 120. Thestorage devices 122 and 124 can be any of a disk storage device (e.g., amagnetic or optical disk storage device), a solid state magnetic device,and so forth. The storage devices 122 and 124 can be the same type ofstorage device or different types of storage devices.

A speaker 132 is operatively coupled to system bus 102 by the soundadapter 130. A transceiver 142 is operatively coupled to system bus 102by network adapter 140. A display device 162 is operatively coupled tosystem bus 102 by display adapter 160.

A first user input device 152, a second user input device 154, and athird user input device 156 are operatively coupled to system bus 102 byuser interface adapter 150. The user input devices 152, 154, and 156 canbe any of a keyboard, a mouse, a keypad, an image capture device, amotion sensing device, a microphone, a device incorporating thefunctionality of at least two of the preceding devices, and so forth. Ofcourse, other types of input devices can also be used, while maintainingthe spirit of the present principles. The user input devices 152, 154,and 156 can be the same type of user input device or different types ofuser input devices. The user input devices 152, 154, and 156 are used toinput and output information to and from system 100.

Of course, the processing system 100 may also include other elements(not shown), as readily contemplated by one of skill in the art, as wellas omit certain elements. For example, various other input devicesand/or output devices can be included in processing system 100,depending upon the particular implementation of the same, as readilyunderstood by one of ordinary skill in the art. For example, varioustypes of wireless and/or wired input and/or output devices can be used.Moreover, additional processors, controllers, memories, and so forth, invarious configurations can also be utilized as readily appreciated byone of ordinary skill in the art. These and other variations of theprocessing system 100 are readily contemplated by one of ordinary skillin the art given the teachings of the present principles providedherein.

Moreover, it is to be appreciated that system 200 described below withrespect to FIG. 2 is a system for implementing respective embodiments ofthe present principles. Part or all of processing system 100 may beimplemented in one or more of the elements of system 200.

Further, it is to be appreciated that processing system 100 may performat least part of the method described herein including, for example, atleast part of method 400 of FIGS. 4-6 and/or at least part of method 700of FIGS. 7-9. Similarly, part or all of system 200 may be used toperform at least part of method 400 of FIGS. 4-6 and/or at least part ofmethod 700 of FIGS. 7-9.

FIG. 2 shows an exemplary system 200 for determining the size of adistribution of aerosols, in accordance with an embodiment of thepresent principles.

The system 200 includes a hyperspectral imaging (HIS) camera 210 (alsointerchangeably referred to as a “hyperspectral camera” in short), alaser diode (or other electromagnetic radiation source) array 220, and adata processing system 230. For the sake of brevity and illustration,the following description will involve laser diodes, noting that thesame can be replaced by other sources of electromagnetic radiationincluding, but not limited to, Tungsten lamps and/or other calibrated(known spectral emission) light emitters. As such, it is to beappreciated that these various sources of electromagnetic radiation areinterchangeably and generally referred to herein as light emitters.

FIG. 3 shows a top view of the laser diode array 220 of FIG. 2, inaccordance with an embodiment of the present principles. It is to beappreciated that any spacing can be used between the elements of thediode array, depending upon the implementation. Similarly, any number ofelements of the diode array can be used, depending upon theimplementation.

In the embodiments of FIGS. 2 and 3, the laser diode array 220 includesa set of laser diodes (collectively and individually denoted by thereference characters “220A”) and a set of black disks (collectively andindividually denoted by the reference characters “220W”). In theembodiments of FIGS. 2 and 3, each of the black disks 220A in the arrayis mounted on a backing material 223 (here, a backing board, althoughany suitable material (e.g., wood, plastic, metal, and so forth) in anyform/shape (e.g., pole, and so forth) can be used, including existingstructure or infrastructure found in a location at which the presentprinciples are to be deployed). Each of the laser diodes 220A is eachmounted and/or otherwise disposed on a respective one of the black disks220B. The pairs formed from each laser diode 220A being mounted on acorresponding black disk 220B can be mounted at any angle relative tothe earth. For example, the flat surface of the black disk 220B in aformed pair can be mounted parallel relative to the earth, perpendicularrelative to the earth, and so forth. The pairs and/or array can bemounted on, but is not limited to, for example, a tower, building, pole,and so forth. The black disks 220B are physical objects that ideallyabsorb all incident electromagnetic radiation, regardless of frequencyor angle of incidence. Hence, as used herein, the term “black disk”refers to a physical disk having at least an externally black body forabsorbing incident electromagnetic radiation.

The hyperspectral camera 210 can collect information as a set of“images”, where each image represents a narrow wavelength range of theelectromagnetic spectrum. These “images” are then combined, by the dataprocessing system 230, to form a three-dimensional (x,y,λ) hyperspectraldata cube for processing and analysis, where x and y represent twospatial dimensions of the scene, and λ represents the spectral dimension(comprising a range of wavelengths). The hyperspectral data cube can beformed using any of the following data acquisition techniques: spatialscanning; spectral scanning; non-scanning (snapshot); andspatio-spectral scanning.

The hyperspectral camera 210 can be mobile or stationary, depending onthe implementation. For example, regarding the former, the hyperspectralcamera 210 can be mounted on a plane, helicopter, drone, and so forth.In such a case, the hyperspectral camera 210 can obtain angularrecordings of the diodes spectra.

Moreover, regarding the latter, the (or another) hyperspectral camera210 can be alternatively or supplementary mounted on, for example, avery tall building (e.g., a skyscraper), and so forth.

The hyperspectral image of the laser diode array 220 can be used toassess the extinction of the laser diode light at different anglesand/or at different wavelengths. Moreover, the hyperspectral image ofthe laser diode array 220 can be used to assess the halo around thelaser diodes in the laser diode array 220 due to scattering, which caninvolve selecting pixels from the black disk and/or screening the laserdiodes.

The data processing system 230 performs data processing of results fromdata collection using the hyperspectral camera 210.

While the embodiment of FIG. 2 shows a single hyperspectral camera, asingle laser diode array and a single data processing system 230, inother embodiments, more than one of any of the preceding elements can beemployed, while maintaining the spirit of the present principles. Inaddition, a well calibrated light source, such as tungsten lamp could beused.

In an embodiment, the present principles can take into account thephysical properties of light scattering by particles (Mie scattering)and how their absorption affects the intensity of light detected atdifferent wave lengths.

In an embodiment, the present principles use the laser diode array 220in the field, where hyperspectral images of the laser diodes and theclose surrounding (halo) generated by the diodes are obtained by thehyperspectral camera 210. During a data collection phase, thehyperspectral camera 210 is located at an appropriate distance todetermine the particle size distribution of the aerosol cloud viaappropriate analytics.

A brief description will now be given regarding some of the parametersgoverning scattering, to which the present principles can be applied,according to an embodiment of the present principles.

(1) The wavelength (λ) of the incident radiation.

(2) The size of the scattering particle, usually expressed as thenon-dimensional size parameter x, as follows:x=(2πr)/λ,where r denotes the radius of a spherical particle, and λ denoteswavelength.

(3) The particle optical properties relative to the surrounding medium:the complex refractive index.

For MIE scattering on particles where the diameter of particles iscomparable to the detection wavelength, x˜1.

A brief description will now be given regarding MIE scattering, to whichthe present principles can be applied, in accordance with an embodimentof the present principles.

MIE theory describes the scattering and absorption of electromagneticradiation by spherical or non-spherical particles though solving Maxwellequations. MIE theory operates on the following assumptions: (1) theparticle size is comparable to the detection wavelength; and (2) theparticle is homogeneous (therefore, it is characterized by a singlerefractive index at a given wavelength).

It is to be appreciated that while the figures provided herein show oneor more laser diodes being used as a source of electromagneticradiation, the present principles are not limited to the same and, thus,other sources of electromagnetic radiation can also be used. Forexample, other types of electromagnetic sources to which the presentprinciples can be applied include, but are not limited to, Tungstenlamps and so forth.

FIGS. 4-6 show an exemplary method 400 for determining the size of adistribution of aerosols using white laser diodes mounted on blackdisks, in accordance with an embodiment of the present principles. Whilethe example of FIGS. 4-6 is described with respect to a single whitelaser diode on a single black disk for the sake of brevity andillustration, the method of FIGS. 4-6 can be readily applied to a diodearray that includes more than one pair formed from a white laser diodeand a black disk as described herein and shown in at least FIGS. 2 and3, as readily appreciated by one of ordinary skill in the art, whilemaintaining the spirit of the present principles. Moreover, as notedabove, in an embodiment, a Tungsten lamp or other light emitter can beused in place of the laser diode. However, for the sake of illustrationand clarity, the example of FIGS. 4-6 are described with respect to alaser diode.

In the embodiment of FIGS. 4-6, steps 405 through 430 are performed in alaboratory or similarly appropriate setting, while steps 435 through 450are performed in the field, as readily appreciated by one of ordinaryskill in the art. Steps 455 through 470 can be performed in any of thepreceding settings. Of course, the steps of method 400 are not limitedto the preceding settings and can be performed in other settings whilemaintaining the spirit of the present principles.

At step 405, record spectral emission from a white laser diode in clearair.

At step 410, record the spectral emission from a black disk in cleanair.

At step 415, record the intensities of the emissions from the whitelaser diode and the black disk in clean air and record the ratio of theintensities of the emissions from the white laser diode and the blackdisk.

At step 420, create libraries of spectral response of the black disk toan aerosol distribution using particles having different well-definedparticle sizes and using different distribution densities, and recordthe angular distribution of the recorded spectra for the narrow aerosoldistribution with the different well-defined particle sizes and thedifferent distribution densities. In an embodiment, step 420 isperformed in a laboratory setting.

At step 425, sort the spectral response and angular distributions basedon particle size.

At step 430, identify polarization angles and emission angles for theparticles having different well-defined particle sizes.

At step 435, record the spectral intensity of the given laser diode asfunction of the angle between the given laser diode and the camera usingthe sensors (other laser diodes in the laser diode array) as referencepoints.

At step 440, record the local temperature.

At step 445, record a reference spectra from a target that may be inclose proximity and above the level of a cloud. This target can be ablack surface that would normally absorb all the light and any signalcan be attributed to scattering from particles situated between theblack surface and detector.

At step 450, define a region of interest 1 (ROI-1) as the laser diode.

At step 455, define a region of interest 2 (ROI-2) as the black disk.While ROI-2 can include both the black disk and its mount, the blackdisk serves as a reference.

At step 460, subtract from the hyperspectral layers of ROI-1, thehyperspectral weight relation of the diode emission or subtract ROI-1from the total hypercube. The system response will have a wavelengthdependence as the scattering at different wavelengths will change. Thechange will be dependent on the size of particles and their chemicalcomposition. The method will acquire the response for multiplewavelength diodes and subtract the black surface signal to createmultiple data points that will approximate the spectral response. Eachwavelength will be one layer in the hypercube that includes individuallayers at different wavelength. The gap between the data points can befitted using polynomial curves to create a continuous spectral response.The spectral response can be compared with a continuous measurement ofparticles of different sizes and chemical properties obtained in thelaboratory using a spectrometer.

At step 465, subtract from the hyperspectral layers of ROI-2, thehyperspectral weight relation of the emission of the black disk at theactual field temperature.

In an embodiment, step 465 includes steps 465A through 465E.

At step 465A, analyze the spectral response of ROI-2.

At step 465B, use the results of the analysis of the spectral responseof ROI-2 (per step 465A) and the spectral response libraries (per step420) as a parameter set for particle size distribution.

At step 465C, compare the total collected intensity per filter of ROI-1and ROI-2. Each wavelength is a filter as it will pass the light in avery narrow band. Additionally the polarization will play a role if theparticles size is not spherical.

At step 465D, compare the intensity of signal from the laser diodesignal with the spectrum obtained at step 415 to determine the densityof the particles per unit volume of air.

At step 465, compare the spectrum from the black disk intensityparameter set (per step 420) to make corrections to the densitydistribution and validate the result from step 465D.

FIGS. 7-9 show an exemplary method 700 for determining the size of adistribution of aerosols using colored laser diodes or white laserdiodes with narrow bandpass filters and polarization filters in front ofthe white laser diodes, in accordance with an embodiment of the presentprinciples. The laser diodes and filters are mounted on black disks.

It is to be appreciated that the use of color laser diodes or whitelaser diodes with narrow bandpass filters and polarization filters infront of the white laser diodes can provide more precision in theinfrared region of the electromagnetic spectrum. In the embodiment ofFIGS. 7-9, the laser diodes have different wavelengths λ₀ definedapproximately by x=2πa/λ₀, where a denotes the approximate radius of theparticles.

In the embodiment of FIGS. 7-9, steps 705 through 720 are performed in alaboratory or similarly appropriate setting, while steps 725 through 735are performed in the field, as readily appreciated by one of ordinaryskill in the art. Step 740 can be performed in any of the precedingsettings. Of course, the steps of method 600 are not limited to thepreceding settings and can be performed in other settings whilemaintaining the spirit of the present principles.

At step 705, record the spectral emission, in clean air, from thecolored laser diodes or the white laser diodes with the narrow bandpassfilters and polarization filters, or block the direct laser diode light.

At step 710, record the spectral emission from the black disks in cleanair.

At step 715, record the intensities of the emissions from the laserdiodes and the black disks in clean air and record the ratio of theintensities of the emissions from the laser diodes and the black disk.

At step 720, create libraries of the spectral response of the blackdisks with respect to a narrow aerosol (e.g., PM2.5) distribution.

At step 725, record the polarization pattern for the aerosols forspecific locations.

At step 730, record the hyperspectral image of the laser diodes.

At step 735, record the local temperature, relative humidity, and watercontent in the air.

At step 740, perform data processing for each of the wavelengths λ₀. Inan embodiment, step 740 includes steps 740A through 740D.

At step 740A, define a region of interest 1 (ROI-1) as the laser diode.

At step 740B, define a region of interest 2 (ROI-2) as the black diskmount.

At step 740C, subtract from the hyperspectral layers of ROI-1, thehyperspectral weight relation of the diode emission, or directly removeROI-1.

At step 740D, subtract from the hyperspectral layers of ROI-2, thehyperspectral weight relation of the emission of the black disks at theactual field temperature.

In an embodiment, step 740D includes steps 740D1 through 740D7.

At step 740D1, analyze the spectral response of ROI-2 for wavelengthsaround λ₀. The spectral response is indicative of the chemicalcomposition of the particles.

At step 740D2, analyze the angular distribution of the spectral responseof ROI-2. The angular distribution is indicative of the verticaldistribution of the particles around the detection source. The highestdensity is expected near the surface and slowly decreasing withaltitude.

At step 740D3, analyze the polarization properties of the spectralresponse of ROI-2. The polarization is an indicative of the shape of theparticles that scatter light.

At step 740D4, use the results of the analysis of the spectral responseof ROI-2 for wavelengths around wavelength λ₀ as a parameter set forparticle size distribution.

At step 740D5, compare total collected intensity per filter aroundwavelength Xo of ROI-1 and ROI-2.

At step 740D6, compare the spectral information obtained from steps 715and 720 with the spectrum obtained from 740 d 5, and compare theintensities at the different wavelengths extracted from 740D5 withwell-known spectral signatures obtained from well-characterized sampleswith known particle size, density, shape and chemical composition, todetermine the density of particles with a certain size distribution.

At step 740D7, compare the parameter set (per step 740D4), the shape ofthe emission, the intensity of the signal, and the polarization responsewith the subset of identified particles extracted in the previous stepand assign a probability for a particle to have certain diameter, shapeand composition based on established responses obtained in thelaboratory setup.

FIG. 10 shows a system 1000 for determining the size of a distributionof aerosols, deployed in an exemplary scenario 1077, in accordance withan embodiment of the present principles. In scenario 1077, twoaeronautical vehicles 1001 and 1002 each include a hyperspectral camera1010 for capturing hyperspectral images from a laser diode array 1020.The laser array 1020 includes pairs of laser diodes 1020A mounted onblack discs 1020B, with each pair then mounted on a pole 1099. Moreover,each of the vehicles 1001 and 1002 include a data processing system 1030for processing the hyperspectral images. Alternatively, the dataprocessing systems 1030 (or a single data processing system) can belocated at a remote site(s).

FIG. 11 shows a system 1100 for determining the size of a distributionof aerosols, deployed in an exemplary scenario 1177, in accordance withan embodiment of the present principles. In scenario 1177, twoaeronautical vehicles 1101 and 1102 each include a hyperspectral camera1110 for capturing hyperspectral images from a laser diode array 1120.The laser array 1120 includes pairs of laser diodes mounted on blackdiscs, with each pair then mounted on a pole 1199 that is then mountedon a tower 1188. Data processing of the hyperspectral images isperformed at a remote site(s). In this way, the weight of a dataprocessing system(s) does not have be carried by the aeronauticalvehicles 1101 and 1102 used to capture the hyperspectral images.

FIG. 12 shows a system 1200 for determining the size of a distributionof aerosols, deployed in an exemplary scenario 1277, in accordance withan embodiment of the present principles. In scenario 1277, aeronauticalvehicle 1201 includes a hyperspectral camera 1210 for capturinghyperspectral images from a laser diode array 1220 disposed on vehicles1202 and 1203. The laser array 1220 includes pairs of laser diodes 1220Amounted on black discs 1220B, with each pair then mounted on a pole 1299that is then mounted on one of the vehicles 1202 and 1203. Dataprocessing of the hyperspectral images is performed at a remote site(s).In this way, the weight of a data processing system(s) does not have becarried by the aeronautical vehicle 1001 used to capture thehyperspectral images.

The mobile source can be a calibration platform where wide angle imagingof a large surface is calibrated based on a pixel that is generated bythe diode that is mounted on the vehicle. The mobile vehicle can bepositioned or moving across a large area, like a city to create snapshotof images, that are stitched together to create a map of the aerosoldistribution across the city. These measurement can be performedmultiple times per days to capture the temporal variations of theaerosols and particulates in the city. The flying imaging system canalso identify the source of pollution based on the density distributionand dispersion of the plumes. It is expected that at the source, theparticles will have a wider distribution in size and be farther apart,and the smaller size particles will be more prevalent as the larger oneswill settle.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Java, Smalltalk, C++ or the like,and conventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Reference in the specification to “one embodiment” or “an embodiment” ofthe present principles, as well as other variations thereof, means thata particular feature, structure, characteristic, and so forth describedin connection with the embodiment is included in at least one embodimentof the present principles. Thus, the appearances of the phrase “in oneembodiment” or “in an embodiment”, as well any other variations,appearing in various places throughout the specification are notnecessarily all referring to the same embodiment.

It is to be appreciated that the use of any of the following “/”,“and/or”, and “at least one of”, for example, in the cases of “A/B”, “Aand/or B” and “at least one of A and B”, is intended to encompass theselection of the first listed option (A) only, or the selection of thesecond listed option (B) only, or the selection of both options (A andB). As a further example, in the cases of “A, B, and/or C” and “at leastone of A, B, and C”, such phrasing is intended to encompass theselection of the first listed option (A) only, or the selection of thesecond listed option (B) only, or the selection of the third listedoption (C) only, or the selection of the first and the second listedoptions (A and B) only, or the selection of the first and third listedoptions (A and C) only, or the selection of the second and third listedoptions (B and C) only, or the selection of all three options (A and Band C). This may be extended, as readily apparent by one of ordinaryskill in this and related arts, for as many items listed.

Having described preferred embodiments of a system and method (which areintended to be illustrative and not limiting), it is noted thatmodifications and variations can be made by persons skilled in the artin light of the above teachings. It is therefore to be understood thatchanges may be made in the particular embodiments disclosed which arewithin the scope of the invention as outlined by the appended claims.Having thus described aspects of the invention, with the details andparticularity required by the patent laws, what is claimed and desiredprotected by Letters Patent is set forth in the appended claims.

What is claimed is:
 1. An aerosol distribution determining system,comprising: a set of light emitters for emitting electromagneticradiation; a hyperspectral imaging camera for capturing hyperspectralimages of the electromagnetic radiation in an absence of and in apresence of an aerosol distribution; a data processing system fordetermining at least one of a size, a vertical density distribution, anda shape of particles in the aerosol distribution based on a spectralresponse, an angular distribution, and a polarization of the aerosoldistribution derived using the hyperspectral images; and a set of blackdisks for absorbing at least a portion of the electromagnetic radiationemitted from the set of light emitters, wherein each of the lightemitters in the set is mounted on a respective one of the black disks.2. The aerosol distribution determining system of claim 1, furthercomprising a spectral response library formed from the hyperspectralimages and defining a plurality of spectral responses, each of theplurality of spectral responses corresponding to an exposure of any ofthe black disks to a respective one of a plurality of differentreference aerosol distributions.
 3. The aerosol distribution determiningsystem of claim 1, wherein the data processing system uses each of theblack disks as a reference point with respect to the hyperspectralimaging camera from which the at least one of the size, the verticaldensity distribution, and the angular distribution of proximate pointsin the aerosol distribution is determined.
 4. The aerosol distributiondetermining system of claim 1, wherein the data processing signalsubtracts a black disk response signal from a laser diode responsesignal, respectively corresponding to a given one of the black disks anda corresponding one of the light emitters mounted thereon, toapproximate a spectral response at a point in the aerosol distributionat which the given one of the black disks and the corresponding one ofthe light emitters are located.
 5. The aerosol distribution determiningsystem of claim 1, wherein each of the hyperspectral images represent arespective wavelength range of the electromagnetic spectrum, and whereinthe data processing system combines the hyperspectral images to form athree-dimensional (x,y,λ) hyperspectral data cube for processing andanalysis, where x and y represent two spatial dimensions of a givenscene, and λ represents a spectral dimension comprising a range ofwavelengths.
 6. The aerosol distribution determining system of claim 1,wherein the hyperspectral camera obtains angular recordings of a spectraof the light emitters, and the data processing system determines theangular distribution of the aerosol distribution using the angularrecordings.
 7. The aerosol distribution determining system of claim 1,wherein the data processing system performs an assessment of respectiveextinctions of the electromagnetic radiation emitted from the lightemitters at, at least one of, different angles and differentwavelengths.
 8. The aerosol distribution determining system of claim 1,wherein the data processing system performs an assessment of respectivehalos around the light emitters due to scattering.
 9. The aerosoldistribution size determining system of claim 8, wherein the assessmentcomprises, at least one of, selecting pixels from at least one of theblack disks and screening at least one of the light emitters.
 10. Theaerosol distribution determining system of claim 1, wherein the dataprocessing system determines the at least one of the size, the verticaldensity distribution, and the shape of the particles in the aerosoldistribution based on electromagnetic radiation scattering at differentwavelengths that is determined using the hyperspectral images.
 11. Theaerosol distribution determining system of claim 1, further comprising aspectral response library formed from the hyperspectral images anddefining a plurality of spectral responses for use in determining thespectral response of the aerosol distribution.
 12. The aerosoldistribution determining system of claim 1, wherein the set of lightemitters form reference points in the aerosol distribution from whichthe data processing system extrapolates the at least one of the size,the vertical density distribution, and the shape of particles in theaerosol distribution for other points in the aerosol distribution.
 13. Amethod for aerosol distribution determination, comprising: emitting, bya set of light emitters, electromagnetic radiation; capturing, by ahyperspectral imaging camera, hyperspectral images of theelectromagnetic radiation in an absence of and in a presence of anaerosol distribution; and determining, by a data processing system, atleast one of a size, a vertical density distribution, and a shape ofparticles in the aerosol distribution based on a spectral response, anangular distribution, and a polarization of the aerosol distributionderived using the hyperspectral images, wherein the method furthercomprises absorbing, by a set of black disks, at least a portion of theelectromagnetic radiation emitted from the set of light emitters, andwherein each of the light emitters in the set is mounted on a respectiveone of the black disks.
 14. The method of claim 13, wherein the dataprocessing system determines the at least one of the size, the verticaldensity distribution, and the shape of the particles in the aerosoldistribution based on electromagnetic radiation scattering at differentwavelengths that is determined using the hyperspectral images.
 15. Themethod of claim 13, further comprising forming a spectral responselibrary from the hyperspectral images that defines a plurality ofspectral responses for use in determining the spectral response of theaerosol distribution.
 16. The method of claim 13, wherein the set oflight emitters form reference points in the aerosol distribution fromwhich the data processing system extrapolates the at least one of thesize, the vertical density distribution, and the shape of particles inthe aerosol distribution for other points in the aerosol distribution.17. The method of claim 13, further comprising a spectral responselibrary formed from the hyperspectral images and defining a plurality ofspectral responses for use in determining the spectral response of theaerosol distribution.
 18. The method of claim 13, wherein the set oflight emitters form reference points in the aerosol distribution fromwhich the data processing system extrapolates the at least one of thesize, the vertical density distribution, and the shape of particles inthe aerosol distribution for other points in the aerosol distribution.19. A computer program product for aerosol distribution determination,the computer program product comprising a non-transitory computerreadable storage medium having program instructions embodied therewith,the program instructions executable by a computer to cause the computerto perform a method comprising: emitting, by a set of light emitters,electromagnetic radiation; capturing, by a hyperspectral imaging camera,hyperspectral images of the electromagnetic radiation in an absence ofand in a presence of an aerosol distribution; and determining, by a dataprocessing system, at least one of a size, a vertical densitydistribution, and a shape of particles in the aerosol distribution basedon a spectral response, an angular distribution, and a polarization ofthe aerosol distribution derived using the hyperspectral images, whereinthe method further comprises absorbing, by a set of black disks, atleast a portion of the electromagnetic radiation emitted from the set oflight emitters, and wherein each of the light emitters in the set ismounted on a respective one of the black disks.